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| Title: | Performance of an ℓ1 Regularized Subspace-based MIMO Channel Estimation with Random Sequences |
| Authors: | Takano, Yasuhiro
Juntti, Markku
Matsumoto, Tad |
| Keywords: | Subspace-based channel estimation
noise whitening
massive MIMO
pilot contamination
compressive sensing |
| Issue Date: | 2015-12-04 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Magazine name: | IEEE Wireless Communications Letters |
| Volume: | 5 |
| Number: | 1 |
| Start page: | 112 |
| End page: | 115 |
| DOI: | 10.1109/LWC.2015.2505727 |
| Abstract: | The conventional ℓ2 multi-burst (MB) channel estimation can achieve the Cramer-Rao bound asymptotically by using the subspace projection. However, the ℓ2 MB technique suffers from the noise enhancement problem if the training sequences (TSs) are not ideally uncorrelated. We clarify that the problem is caused by an inaccurate noise whitening process. The ℓ1 regularized MB channel estimation can, however, improve the problem by a channel impulse response length constraint. Asymptotic performance analysis shows that the ℓ1 MB can improve channel estimation performance significantly over the ℓ2 MB technique in a massive multiple-input multiple-output system when the TSs are not long enough and not ideally uncorrelated. |
| Rights: | This is the author's version of the work. Copyright (C) 2015 IEEE. IEEE Wireless Communications Letters, 5(1), 2015, pp.112-115. DOI:10.1109/LWC.2015.2505727. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| URI: | http://hdl.handle.net/10119/12999 |
| Material Type: | author |
| Appears in Collections: | b10-1. 雑誌掲載論文 (Journal Articles)
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